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• Viral integration analysis of hepatocellular carcinoma using virus capture sequence.

  Hepatitis B viral (HBV) DNA is frequently integrated into the genome of hepatocellular carcinoma (HCC) in patients with chronic HBV infection (chronic HBV, hereafter), whereas it is yet to be clarified in patients after HBV disappearance (prior HBV, hereafter). This study aimed to identify viral integration such as HBV and adeno-associated virus type 2 (AAV2) into the HCC genome as oncogenic event.

  Study JGAS000194

• Total RNAseq in the sporadic ALS and healthy control motor cortex

  Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease characterized by the degeneration of upper and lower motor neurons leading to progressive muscle weakness, wasting and paralysis that result in death within a few years from disease onset. In order to characterize RNA alterations in ALS, total RNAseq was performed in the ALS motor cortex, which is an early and vulnerable region in ALS.

  Study EGAS00001004286

• Selenium Chemoprevention: Benefits and Harms

  Selenium is a trace element that may have anti-carcinogenetic effect, but heterogenous treatment effects have been observed. This genome-wide association study investigates if genetic variation modifies the effect of selenium chemoprevention in the Selenium and Celecoxib Trial, a randomized, double-blind, placebo-controlled trial conducted at the University of Arizona Cancer Center. The objective of the clinical trial was to determine whether daily intake of 200 µg/d of selenium as a supplement could reduce the risk for developing metachronous colorectal adenomas. The study participants were recruited between 2001 and 2011. Genome-wide association study was performed for 1,323 study participants who provided blood sample at the time of study entry.

  Study phs002283

• NHLBI TOPMed - NHGRI CCDG: UCSF Atrial Fibrillation Study

  The University of California San Francisco (UCSF) Cardiovascular Research Institute (CVRI) Resource in Arteriosclerosis and Metabolic Disease is an ongoing multi-ethnic study of adults ≥ 18 years of age which was started in 1989 and now includes 28,000 participants recruited from the UCSF medical system. Within the Resource lies data and biospecimens from nearly 1,000 patients presenting to the electrophysiology laboratory for electrophysiology procedures that were densely phenotyped for electrophysiologic characteristics with biospecimens collected from various intra and extra-cardiac chambers. Phenotyping of all participants was achieved via interview and review of medical records. A subset of 113 participants with early-onset atrial fibrillation underwent WGS as a part of the TOPMed Program.

  Study phs001933

• ROBUST (NCT02285062)

  The ROBUST clinical trial is a Phase III, randomized, double-blind, placebo-controlled study designed to compare the efficacy and safety of lenalidomide plus R-CHOP chemotherapy (R2-CHOP) versus placebo plus R-CHOP in newly diagnosed Diffuse Large B-cell Lymphoma (DLBCL). Molecular data was collected for all patients at screening, but the only patients of the Activated B-cell (ABC) cell-of-origin subtype were eligible for study inclusion and clinical follow-up. We have performed unsupervised clustering on this cohort and identified 7 novel transcriptional subtypes of DLBCL, one of which represents a high-risk subset of patients with high MYC expression, ABC-associated biology, and low immune infiltration.

  Study EGAS50000000333

• RRBS sequencing of 7 tumour regions and a normal sample from a single TRACERx patient.

  Background: Epigenetic heterogeneity within a tumour can play an important role in tumour evolution and the emergence of resistance to treatment. It is increasingly recognised that the study of DNA methylation (DNAm) patterns along the genome - so-called `epialleles' - offers greater insight into epigenetic dynamics than conventional analyses which examine DNAm marks individually. Results: We have developed a Bayesian model to infer which epialleles are present in multiple regions of the same tumour. We apply our method to reduced representation bisulfite sequencing (RRBS) data from multiple regions of one lung cancer tumour and a matched normal sample. The model borrows information from all tumour regions to leverage greater statistical power. The total number of epialleles, the epiallele DNAm patterns, and a noise hyperparameter are all automatically inferred from the data. Uncertainty as to which epiallele an observed sequencing read originated from is explicitly incorporated by marginalising over the appropriate posterior densities. The degree to which tumour samples are contaminated with normal tissue can be estimated and corrected for. By tracing the distribution of epialleles throughout the tumour we can infer the phylogenetic history of the tumour, identify epialleles that differ between normal and cancer tissue, and define a measure of global epigenetic disorder. Conclusions: Detection and comparison of epialleles within multiple tumour regions enables phylogenetic analyses, identification of differentially expressed epialleles, and provides a measure of epigenetic heterogeneity.

  Study EGAS00001002484

• Type 1 Diabetes Genetics Consortium (T1DGC): Multi-Ethnic ImmunoChip Study

  Type 1 diabetes (T1D) is characterized by an autoimmune attack that destroys the insulin-producing pancreatic beta cells and is driven by diverse genetic and environmental factors. Between 8-100 chromosome regions are known to contain variants that alter T1D risk, substantially fewer than many other common diseases. Less is known about the contribution of T1D risk alleles in non-European populations, despite recent increases in T1D diagnoses in multiple non-European ancestry groups. To address these gaps in T1D genetics, we doubled the sample size from the previous largest T1D association study, genotyped ancestrally diverse T1D cases, controls, and affected families with the Illumina ImmunoChip array, and imputed additional variants using a large haplotype reference panel. After quality filtering, a total of 61,427 participants and 140,333 genotyped ImmunoChip variants were included in analysis, providing dense coverage in 188 autosomal regions ("ImmunoChip regions") and sparse genotyping in other regions of the genome. Each participant was assigned to one of five ancestry groups using k-means clustering of ImmunoChip genotype principal components: European (EUR, N = 47,319), African Admixed (AFR, N = 4,290), Finnish (FIN, N = 6,991), East Asian (EAS, N = 588) and Other Admixed (AMR, N = 2,239). In total, 16,159 T1D cases, 25,386 controls (unrelated) and 6,143 trio families (i.e., an affected child and both parents) were genotyped and included in association analyses. Imputation with the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) multi-ethnic reference panel was used to improve discovery power and fine-mapping resolution. After imputation, the number of variants in ImmunoChip regions with imputation R-squared > 0.8 and MAF > 0.005 in each ancestry group was 322,084 (AFR), 166,274 (EUR), 163,612 (FIN), 137,730 (EAS) and 188,550 (AMR). Imputed genotypes were compared in the same participants who have whole genome sequencing data, resulting in high concordance. Unrelated cases and controls (N = 41,545) were analyzed initially, assuming an additive inheritance model. T1D trio families (N = 6,143 trios, some trio families were multiplex and analyzed as multiple trios) were analyzed separately, with meta-analysis of case-control and trio results used for discovery of regions associated with T1D (p < 5×10-8). Summary-level data at each SNP (genotype and imputed) for type 1 diabetes (outcome) are provided in dbGaP.

  Study phs002468

• Pheno-Seq, linking 3D phenotypes of clonal tumor spheroids to gene expression

  3D-culture systems have advanced cancer modeling by reflecting physiological characteristics of in-vivo tissues, but our understanding of functional intratumor heterogeneity including visual phenotypes and underlying gene expression is still limited. Transcriptional heterogeneity can be dissected by single-cell RNA-sequencing, but these technologies suffer from low RNA-input and fail to directly correlate gene expression with contextual cellular phenotypes. Here we present pheno-seq for integrated high-throughput imaging and transcriptomic profiling of clonal tumor spheroids derived from 3D models of breast and colorectal cancer. Specifically, we identify characteristic expression signatures that are associated with heterogeneous invasive and proliferative behavior including a rare cell subtype. Furthermore, we identify functionally relevant transcriptional regulators missed by single-cell RNA-seq, link visual phenotypes defined by heterogenous expression to inhibitor response and infer single-cell regulatory states by deconvolution. We anticipate that directly linking molecular features with patho-phenotypes of cancer cells will improve the understanding of intratumor heterogeneity and consequently prove to be useful for translational research.

  Study EGAS00001002999

• SCLC

  The aim of this study is to use sequence data generated from 500 bp paired end reads using the Illumina platform to characterise the breakpoints of chromosomal translocations, amplifications and deletions at high resolution (to the bp).

  Study EGAS00001000009

• Y_chromosome_mis_segregation_in_the_DLD_1_cell_line

  Study of the well-established DLD-1 colorectal cancer cell line, engineered with an inactivatable Y centromere that leads to mis-segregation. The goal is to gain insights into the mechanism of chromothripsis due to chromosome mis-segration.

  Study EGAS00001002551